Abstract: There is disclosed a computing apparatus, including: a memory; a memory encryption controller to encrypt at least a region of the memory; and a network interface to communicatively couple the computing apparatus to a remote host; wherein the memory encryption controller is configured to send an encrypted packet decryptable via an encryption key directly from the memory to the remote host via the network interface, bypassing a network protocol stack.

Abstract: There is disclosed a computing apparatus, including: a memory; a memory encryption controller to encrypt at least a region of the memory; and a network interface to communicatively couple the computing apparatus to a remote host; wherein the memory encryption controller is configured to send an encrypted packet decryptable via an encryption key directly from the memory to the remote host via the network interface, bypassing a network protocol stack.

Abstract: Techniques for dynamically adapting cloud applications are described. A current value of a Key Performance Indicator (KPI) of an executing cloud service instance of a cloud application is detected. A determination is made as to whether the current value of the KPI is unacceptable (e.g., either it is outside of an acceptable range or is within an adaptation region). If the current value of the KPI is unacceptable, a first application programming interface (API) is invoked to request a cloud service instance monitor to adapt the cloud service instance to operate within an acceptable KPI range. If the cloud service instance monitor was unsuccessful, the unacceptable KPI is escalated to the cloud service monitor for the type of the cloud service instance. If the cloud service monitor is unsuccessful, the unacceptable KPI is escalated to the application monitor.

Abstract: An input/output (I/O) device arranged to receive an information element including a payload, determine control information from the information element, classify the information element based on the control information, and issue a write to one of a plurality of computer-readable media based on the classification of the information element, the write to cause the payload to be written to the one of the plurality of computer-readable media.

Abstract: Technologies for datacenter management include one or more computing racks each including a rack controller. The rack controller may receive system, performance, or health metrics for the components of the computing rack. The rack controller generates regression models to predict component lifespan and may predict logical machine lifespans based on the lifespan of the included hardware components. The rack controller may generate notifications or schedule maintenance sessions based on remaining component or logical machine lifespans. The rack controller may compose logical machines using components having similar remaining lifespans. In some embodiments the rack controller may validate a service level agreement prior to executing an application based on the probability of component failure. A management interface may generate an interactive visualization of the system state and optimize the datacenter schedule based on optimization rules derived from human input in response to the visualization.

Abstract: One embodiment provides an apparatus. The apparatus includes ranker logic. The ranker logic is to rank each of a plurality of compute nodes in a data center based, at least in part, on a respective node score. Each node score is determined based, at least in part, on a utilization (U), a saturation parameter (S) and a capacity factor (Ci). The capacity factor is determined based, at least in part, on a sold capacity (Cs) related to the compute node. The ranker logic is further to select one compute node with a highest node score for placement of a received workload.

Abstract: A system comprises a scoring engine comprising at least one processor and memory. The scoring engine is to generate, based on telemetry information obtained from a plurality of nodes of a computing infrastructure, a first availability score for a first node of the plurality of computing infrastructure nodes and a second availability score for a second node of the plurality of computing infrastructure nodes. The scoring engine is further to generate, based on the first availability score of the first computing infrastructure node and the second availability score of the second computing infrastructure node, an edge tension score for a link between the first node and the second node.

Abstract: Examples may include techniques for allocating configurable computing resources from a pool of configurable computing resources to a logical server or virtual machine. The logical server or virtual machine may use allocated configurable computing resources to implement, execute or run a workload.

Abstract: Examples are described for computing resource discovery and management for a system of configurable computing resources that may include disaggregate physical elements such as central processing units, storage devices, memory devices, network input/output devices or network switches. In some examples, these disaggregate physical elements may be located within one or more racks of a data center.

Abstract: In one embodiment, a system comprises a scoring engine comprising at least one processor and memory. The scoring engine is to generate, based on telemetry information obtained from a plurality of nodes of a computing infrastructure, a first availability score for a first node of the plurality of computing infrastructure nodes and a second availability score for a second node of the plurality of computing infrastructure nodes. The scoring engine is further to generate, based on the first availability score of the first computing infrastructure node and the second availability score of the second computing infrastructure node, an edge tension score for a link between the first node and the second node.

Abstract: Embodiments may be generally directed to techniques to receive rate meter information indicating an occurrence of a rate meter event, the rate meter event determined by a rate meter associated with a network element in a software defined network (SDN) environment. determine a requirement for a service provided by the network element is not met based on the rate meter event detected by the rate meter. Embodiments may also include techniques to determine a corrective action based on the requirement not met, the corrective action to cause the requirement to be met for the service provided by the network element in the SDN environment and cause the correct action to be performed for the network element.

Abstract: Embodiments may be generally directed to techniques to cause communication of one or more packets from one or more network interfaces to one or more other network interfaces through a virtual machine monitor, determine at least one of latency and jitter for the virtual machine monitor based, at least in part, on each of the one or more packets communicated through the virtual machine monitor, and perform a corrective action when at least one of the latency and the jitter does not meet a requirement for a virtual machine on the virtual machine monitor.

Abstract: A system comprises a scoring engine comprising at least one processor and memory. The scoring engine is to generate, based on telemetry information obtained from a plurality of nodes of a computing infrastructure, a first availability score for a first node of the plurality of computing infrastructure nodes and a second availability score for a second node of the plurality of computing infrastructure nodes. The scoring engine is further to generate, based on the first availability score of the first computing infrastructure node and the second availability score of the second computing infrastructure node, an edge tension score for a link between the first node and the second node.

Abstract: An input/output (I/O) device arranged to receive an information element including a payload, determine control information from the information element, classify the information element based on the control information, and issue a write to one of a plurality of computer-readable media based on the classification of the information element, the write to cause the payload to be written to the one of the plurality of computer-readable media.

Abstract: An embodiment includes an automatic policy managed password management system. One embodiment manages changing the password (with little to no user interaction) every set number of days. Also, password changes can be made within a set amount of time from the password being viewed by a user. Further, an embodiment includes a web service that contains an “insert record” method to insert a password management record into a managed machine and/or database with no “pre-work” required to use the web service. For example, no record needs to be created on a database and/or managed machines in advance of deploying passwords via the web service. The web service can be pushed to various machines and when the web service starts up, it may insert its own record into a database or managed client. This allows for scalability. Other embodiments are described herein.

Abstract: Techniques for dynamically adapting cloud applications are described. A current value of a Key Performance Indicator (KPI) of an executing cloud service instance of a cloud application is detected. A determination is made as to whether the current value of the KPI is unacceptable (e.g., either it is outside of an acceptable range or is within an adaptation region). If the current value of the KPI is unacceptable, a first application programming interface (API) is invoked to request a cloud service instance monitor to adapt the cloud service instance to operate within an acceptable KPI range. If the cloud service instance monitor was unsuccessful, the unacceptable KPI is escalated to the cloud service monitor for the type of the cloud service instance. If the cloud service monitor is unsuccessful, the unacceptable KPI is escalated to the application monitor.

Abstract: Examples are described for computing resource discovery and management for a system of configurable computing resources that may include disaggregate physical elements such as central processing units, storage devices, memory devices, network input/output devices or network switches. In some examples, these disaggregate physical elements may be located within one or more racks of a data center.

Abstract: In one embodiment, a system comprises a scoring engine comprising at least one processor and memory. The scoring engine is to generate, based on telemetry information obtained from a plurality of nodes of a computing infrastructure, a first availability score for a first node of the plurality of computing infrastructure nodes and a second availability score for a second node of the plurality of computing infrastructure nodes. The scoring engine is further to generate, based on the first availability score of the first computing infrastructure node and the second availability score of the second computing infrastructure node, an edge tension score for a link between the first node and the second node.

Abstract: One embodiment provides an apparatus. The apparatus includes ranker logic. The ranker logic is to rank each of a plurality of compute nodes in a data center based, at least in part, on a respective node score. Each node score is determined based, at least in part, on a utilization (U), a saturation parameter (S) and a capacity factor (Ci). The capacity factor is determined based, at least in part, on a sold capacity (Cs) related to the compute node. The ranker logic is further to select one compute node with a highest node score for placement of a received workload.

Abstract: Examples include techniques to generate workload performance fingerprints for cloud infrastructure elements. In some examples, performance metrics are obtained from resource elements or nodes included in an identified sub-graph that represents at least a portion of configurable computing resources of a cloud infrastructure. For these examples, averages for the performance metrics are determined and then stored at a top-level context information node for the identified sub-graph to represent a workload performance fingerprint for the identified sub-graph.